Conformational heterogeneity of the voltage sensor loop of KvAP in micelles and membranes: A fluorescence approach

KvAP is a tetrameric voltage-gated potassium channel that is composed of a pore domain and a voltage-sensing domain (VSD). The VSD is crucial for sensing transmembrane potential and gating. At 0 mV, the VSD adopts an activated conformation in both n-octylglucoside (OG) micelles and phospholipid membranes. Importantly, gating-modifier toxins that bind at S3b-S4 loop of KvAP-VSD exhibit pronounced differences in binding affinity in these membrane-mimetic systems. However, the conformational heterogeneity of this functionally-important sensor loop in membrane mimetics is poorly understood, and is the focus of this work. In this paper, we establish, using intrinsic fluorescence of the uniquely positioned W70 in KvAP-VSD and environment-sensitive NBD (7-nitrobenz-2-oxa-1,3-diazol-4-yl-ethylenediamine) fluorescence of the labelled S3b-S4 loop, that the surface charge of the membrane does not significantly affect the topology and structural dynamics of the sensor loop in membranes. Importantly, the dynamic variability of the sensor loop is preserved in both zwitterionic (POPC) and anionic (POPC/POPG) membranes. Further, the lifetime distribution analysis for the NBD-labelled residues by maximum entropy method (MEM) demonstrates that, in contrast to micelles, the membrane environment not only reduces the relative discrete population of sensor loop conformations, but also broadens the lifetime distribution peaks. Overall, our results strongly suggest that the conformational heterogeneity of the sensor loop is significantly altered in membranes and this correlates well with its environmental heterogeneity. This constitutes the first report demonstrating that MEM-lifetime distribution could be a powerful tool to distinguish changes in conformational heterogeneity in potassium channels with similar architecture and topology.

Strong anisotropic lifetime orientation distributions of a two-level quantum emitter around a plasmonic nanorod

Spontaneous emission lifetime orientation distributions of a two-level quantum emitter in metallic nanorod structures are theoretically investigated by the rigorous electromagnetic Green function method. It was found that spontaneous emission lifetime strongly depended on the transition dipole orientation and the position of the emitter. The anisotropic factor defined as the ratio between the maximum and minimum values of the lifetimes along different dipole orientations can reach up to 10(3). It is much larger than those in dielectric structures which are only several times usually. Our results show that the localized plasmonic resonance effect provides a new degree of freedom to effectively control spontaneous emission by the dipole orientation of the quantum emitters.

Bayesian lead time estimation for the Johns Hopkins Lung Project data

Problem statement: Lung cancer screening using X-rays has been controversial for many years. A major concern is whether lung cancer screening really brings any survival benefits, which depends on effective treatment after early detection. The problem was analyzed from a different point of view and estimates were presented of the projected lead time for participants in a lung cancer screening program using the Johns Hopkins Lung Project (JHLP) data.

Method: The newly developed method of lead time estimation was applied where the lifetime T was treated as a random variable rather than a fixed value, resulting in the number of future screenings for a given individual is a random variable. Using the actuarial life table available from the United States Social Security Administration, the lifetime distribution was first obtained, then the lead time distribution was projected using the JHLP data.

Results: The data analysis with the JHLP data shows that, for a male heavy smoker with initial screening ages at 50, 60, and 70, the probability of no-early-detection with semiannual screens will be 32.16%, 32.45%, and 33.17%, respectively; while the mean lead time is 1.36, 1.33 and 1.23 years. The probability of no-early-detection increases monotonically when the screening interval increases, and it increases slightly as the initial age increases for the same screening interval. The mean lead time and its standard error decrease when the screening interval increases for all age groups, and both decrease when initial age increases with the same screening interval.

Conclusion: The overall mean lead time estimated with a random lifetime T is slightly less than that with a fixed value of T. This result is hoped to be of benefit to improve current screening programs.